Abstract: The disclosure relates to double stranded ribonucleic acid (dsRNAi) agents and compositions targeting a leucine-rich repeat kinase 2 (LRRK2) gene, as well as methods of inhibiting expression of a LRRK2 gene and methods of treating subjects having a LRRK2-associated disease or disorder, e.g., Parkinson's disease, using such dsRNAi agents and compositions.

Abstract: The disclosure relates to double-stranded ribonucleic acid (dsRNA) agents and compositions targeting the ATXN3 gene, as well as methods of inhibiting expression of an APP gene and methods of treating subjects having an ATXN3-associated disease or disorder, such as SCA3, using such dsRNA agents and compositions.

Abstract: A technique and device (12) may be utilized to determine a characteristic of a crystallographic texture of a sample (10) based on a detected ultrasonic waveform. The device may be configured to receive ultrasonic waveform data representative of a reflected ultrasonic waveform that propagated through a sample from an ultrasonic detector (14). The device may select a portion of the ultrasonic waveform data and apply a Fast Fourier Transform to the portion of the ultrasonic waveform data to transform the portion from a time domain to a frequency domain. The device then may identify a dominant frequency (98) of the portion in the frequency domain and determine a characteristic of a crystallographic texture for the portion based on the dominant frequency of the portion.

Abstract: A system may include a data analysis device that is configured to receive from an ultrasonic waveform detector ultrasonic waveform data representative of an ultrasonic waveform that propagated through a sample and resonated within a defect within the sample. The data analysis device may be further configured to select a portion of the ultrasonic waveform data, apply a Fast Fourier Transform to the portion of the ultrasonic waveform data to transform the portion from a time domain to a frequency domain, identify a characteristic frequency of the portion in the frequency domain, and determine a characteristic of the defect based on the characteristic frequency of the portion. In some examples, the characteristic of the defect may be at least one of an approximate size or an approximate shape of the defect.

Abstract: A system may include a data analysis device that is configured to receive from an ultrasonic waveform detector ultrasonic waveform data representative of an ultrasonic waveform that propagated through a sample and resonated within a defect within the sample. The data analysis device may be further configured to select a portion of the ultrasonic waveform data, apply a Fast Fourier Transform to the portion of the ultrasonic waveform data to transform the portion from a time domain to a frequency domain, identify a characteristic frequency of the portion in the frequency domain, and determine a characteristic of the defect based on the characteristic frequency of the portion. In some examples, the characteristic of the defect may be at least one of an approximate size or an approximate shape of the defect.

Abstract: A technique and device (12) may be utilized to determine a characteristic of a crystallographic texture of a sample (10) based on a detected ultrasonic waveform. The device may be configured to receive ultrasonic waveform data representative of a reflected ultrasonic waveform that propagated through a sample from an ultrasonic detector (14). The device may select a portion of the ultrasonic waveform data and apply a Fast Fourier Transform to the portion of the ultrasonic waveform data to transform the portion from a time domain to a frequency domain. The device then may identify a dominant frequency (98) of the portion in the frequency domain and determine a characteristic of a crystallographic texture for the portion based on the dominant frequency of the portion.